Getting started: few seconds to PyToune

The core data structure of PyToune is a Model, a way to train your own PyTorch neural networks.

How PyToune works is that you create your PyTorch module (neural network) as usual but when comes the time to train it you feed it into the PyToune Model, which handles all the steps, stats and callbacks, similar to what Keras does.

You can evaluate the performances of your network using the evaluate method of PyToune's model;

loss_and_metrics = model.evaluate(x_test, y_test)

Or only predict on new data;

predictions = model.predict(x_test)

As you can see, PyToune is inspired a lot by the friendliness of Keras. See the PyToune documentation at PyToune.org for more.

Installation

Before installing PyToune, you must have a working version of PyTorch 0.3.0 in your environment.

Install the stable version of PyToune:

pip install pytoune

Install the latest version of PyToune:

pip install -U git+https://github.com/GRAAL-Research/pytoune.git

Why this name, PyToune?

PyToune (or pitoune in Québécois) used to be wood logs that flowed through the rivers. It was an efficient way to travel large pieces of wood across the country. We hope that PyToune will make your PyTorch neural networks training flow easily just like the "pitounes" used to.